5 Misconceptions of AI

2023 is the year of AI. AI has definitely spurred up the world this year, particularly the tech industry. However, there are also many myths and misunderstandings about what AI can and cannot do, how it works, and what its implications are. Almost every other tech products you have came across this year, have probably been branded with terms such as “powered by AI”, “with AI”, “AI-powered” and etc. It begs the question of how many of those are truly built with AI technology and how many of those are merely gimmicky marketing terms. To tell them apart, one has to truly understand AI fundamentally. In this blog post, we will debunk five common misconceptions of AI and provide some facts and insights to help you better understand this fascinating technology fundamentally.

Misconception 1 : AI is a single entity or a monolithic system

AI is not a single thing, but rather a broad term that encompasses many different subfields, methods, tools, and systems. AI can be divided into narrow AI, which is designed to perform specific tasks such as image recognition or natural language processing; general AI, which is the hypothetical ability to perform any intellectual task that a human can, and super AI, which can surpass human intelligence in every aspect. General AI and super AI do not exist yet, and may only be achieved through quantum computing, while narrow AI is already widely used in various domains such as healthcare, education, entertainment, and security.

AI can also be classified into symbolic AI, which uses logic and rules to represent knowledge, and sub-symbolic AI, which uses numerical methods such as neural networks and machine learning to learn from data. AI can be applied to various domains such as computer vision, natural language processing, robotics, gaming, healthcare, education and more. Therefore, AI is not a single technology or a monolithic entity, but a diverse and evolving field of study and practice.

Misconception 2 : AI can understand human emotions and intentions

AI can analyse human behavior and speech using techniques such as sentiment analysis, facial expression recognition, and natural language understanding. However, this does not mean that AI can truly comprehend or empathize with human emotions and intentions. AI systems are based on data and algorithms, not on feelings or values. They do not have emotions or motivations of their own, and they cannot explain why they make certain decisions or actions.

For example, AI can analyze the syntax or sentiment of a text or speech, but it cannot grasp the meaning, context, intention or implication of the words or expressions. AI can also recognize facial expressions or voice tones, but it cannot infer the emotions or feelings behind them. AI can mimic natural language or human emotions, but it cannot generate them spontaneously or authentically.

Theoretically, a sentient AI that can understand human emotions and intentions, can only be achieved through quantum computing. However, quantum computing is still very much in research phase where big tech companies like Microsoft and Google are actively developing prototypes of quantum computer. 

Misconception 3 : AI will replace humans in all jobs and activities

AI will undoubtedly have a significant impact on the future of work and society, but it will not replace humans in all jobs and activities. Rather, it will augment human capabilities and create new opportunities for collaboration and innovation. AI can perform tasks that are repetitive, tedious, or dangerous for humans, such as data analysis, quality control, or fraud detection. However, it cannot replace human creativity, judgment, intuition, or social skills, which are essential for many professions and domains such as art, science, education, or leadership. Moreover, AI will also create new jobs and roles that require human oversight, maintenance, or interaction with AI systems. AI is not smarter than humans in a general sense, but only in specific domains or tasks where it has been trained or designed to perform well.  For example, AI can beat humans in chess or Go, but it cannot understand the meaning or context of the game, nor can it transfer its skills to other domains. AI is not a threat to human intelligence or superiority, but a tool that can augment and complement human capabilities.

Misconception 4 : AI is a threat to humanity

AI is often portrayed as a threat to humanity in popular culture and media, such as in movies or books that depict scenarios where AI becomes evil or rebellious and tries to harm or enslave humans. However, this is a very unrealistic and sensationalized view of AI. As mentioned earlier, AI does not have emotions or intentions of its own, and it is not inherently good or evil. It is a tool that can be used for good or bad purposes depending on how it is developed and deployed by humans. Therefore, the real challenge is not to fear or fight against AI, but to ensure that it is aligned with human values and ethics, and that it is used responsibly and beneficially for society.

Misconception 5 : AI is always objective and fair

AI is often perceived as being objective and fair because it is based on data and logic. However, this is not necessarily true. AI systems can inherit the biases and errors of the data they are trained on, the algorithms they use, or the people who design or use them. For example, AI can inherit the biases or errors of the data it is trained on, such as racial, gender or cultural stereotypes. AI can also amplify the biases or errors of the algorithms it uses, such as favoring certain outcomes or groups over others. AI can also be influenced by the values or goals of its creators and users, such as maximizing profit or power at the expense of ethics or fairness. Therefore, it is crucial to ensure that the data and algorithms used by AI systems are transparent, reliable, and representative of the intended users and contexts. 

Data is the foundation, the fuel of AI systems. We do not know for sure how AI will transform and evolve construction industry and the best thing we could do right now is to put transparent, reliable and representative data in your hands. Our goal at BCISM has always been about providing accurate and reliable cost data that serves as a foundation for what our users do. A supercar that runs on low-grade fuel will never gives you the best performance it can achieve. Our goal is to provide you the best fuel possible.


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